Data Profile Report

Dataset statistics

Number of variables	16
Number of observations	700
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	87.6 KiB
Average record size in memory	128.2 B

Variable types

Categorical	6
Numeric	9
DateTime	1

Warnings

`Gross Sales` is highly correlated with `Sales` and 1 other fields	High correlation
`Sales` is highly correlated with `Gross Sales` and 1 other fields	High correlation
`COGS` is highly correlated with `Gross Sales` and 1 other fields	High correlation
`Country` is uniformly distributed	Uniform
`Discounts` has 53 (7.6%) zeros	Zeros

Reproduction

Analysis started	2021-02-24 10:41:27.118940
Analysis finished	2021-02-24 10:41:42.130377
Duration	15.01 seconds
Software version	pandas-profiling v2.11.0
Download configuration	config.yaml

Segment
Categorical

Distinct	5
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Government	300
Enterprise	100
Channel Partners	100
Small Business	100
Midmarket	100

Length

Max length	16
Median length	10
Mean length	11.28571429
Min length	9

Characters and Unicode

Total characters	7900
Distinct characters	24
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Government
2nd row	Government
3rd row	Midmarket
4th row	Midmarket
5th row	Midmarket

Value	Count	Frequency (%)
Government	300	42.9%
Enterprise	100	14.3%
Channel Partners	100	14.3%
Small Business	100	14.3%
Midmarket	100	14.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
government	300	33.3%
enterprise	100	11.1%
small	100	11.1%
partners	100	11.1%
channel	100	11.1%
business	100	11.1%
midmarket	100	11.1%

Most occurring characters

Value	Count	Frequency (%)
e	1200	15.2%
n	1100	13.9%
r	800	10.1%
t	600	7.6%
m	500	6.3%
s	500	6.3%
a	400	5.1%
G	300	3.8%
o	300	3.8%
v	300	3.8%
Other values (14)	1900	24.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6800	86.1%
Uppercase Letter	900	11.4%
Space Separator	200	2.5%

Most frequent character per category

Value	Count	Frequency (%)
e	1200	17.6%
n	1100	16.2%
r	800	11.8%
t	600	8.8%
m	500	7.4%
s	500	7.4%
a	400	5.9%
o	300	4.4%
v	300	4.4%
i	300	4.4%
Other values (6)	800	11.8%

Value	Count	Frequency (%)
G	300	33.3%
M	100	11.1%
C	100	11.1%
P	100	11.1%
E	100	11.1%
S	100	11.1%
B	100	11.1%

Value	Count	Frequency (%)
	200	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7700	97.5%
Common	200	2.5%

Most frequent character per script

Value	Count	Frequency (%)
e	1200	15.6%
n	1100	14.3%
r	800	10.4%
t	600	7.8%
m	500	6.5%
s	500	6.5%
a	400	5.2%
G	300	3.9%
o	300	3.9%
v	300	3.9%
Other values (13)	1700	22.1%

Value	Count	Frequency (%)
	200	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7900	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	1200	15.2%
n	1100	13.9%
r	800	10.1%
t	600	7.6%
m	500	6.3%
s	500	6.3%
a	400	5.1%
G	300	3.8%
o	300	3.8%
v	300	3.8%
Other values (14)	1900	24.1%

Country
Categorical

UNIFORM

Distinct	5
Distinct (%)	0.7%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

United States of America	140
Germany	140
Canada	140
France	140
Mexico	140

Length

Max length	24
Median length	6
Mean length	9.8
Min length	6

Characters and Unicode

Total characters	6860
Distinct characters	22
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Canada
2nd row	Germany
3rd row	France
4th row	Germany
5th row	Mexico

Value	Count	Frequency (%)
United States of America	140	20.0%
Germany	140	20.0%
Canada	140	20.0%
France	140	20.0%
Mexico	140	20.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
united	140	12.5%
of	140	12.5%
states	140	12.5%
mexico	140	12.5%
germany	140	12.5%
france	140	12.5%
america	140	12.5%
canada	140	12.5%

Most occurring characters

Value	Count	Frequency (%)
a	980	14.3%
e	840	12.2%
n	560	8.2%
r	420	6.1%
c	420	6.1%
i	420	6.1%
t	420	6.1%
	420	6.1%
d	280	4.1%
m	280	4.1%
Other values (12)	1820	26.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5460	79.6%
Uppercase Letter	980	14.3%
Space Separator	420	6.1%

Most frequent character per category

Value	Count	Frequency (%)
a	980	17.9%
e	840	15.4%
n	560	10.3%
r	420	7.7%
c	420	7.7%
i	420	7.7%
t	420	7.7%
d	280	5.1%
m	280	5.1%
o	280	5.1%
Other values (4)	560	10.3%

Value	Count	Frequency (%)
C	140	14.3%
G	140	14.3%
F	140	14.3%
M	140	14.3%
U	140	14.3%
S	140	14.3%
A	140	14.3%

Value	Count	Frequency (%)
	420	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6440	93.9%
Common	420	6.1%

Most frequent character per script

Value	Count	Frequency (%)
a	980	15.2%
e	840	13.0%
n	560	8.7%
r	420	6.5%
c	420	6.5%
i	420	6.5%
t	420	6.5%
d	280	4.3%
m	280	4.3%
o	280	4.3%
Other values (11)	1540	23.9%

Value	Count	Frequency (%)
	420	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6860	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	980	14.3%
e	840	12.2%
n	560	8.2%
r	420	6.1%
c	420	6.1%
i	420	6.1%
t	420	6.1%
	420	6.1%
d	280	4.1%
m	280	4.1%
Other values (12)	1820	26.5%

Product
Categorical

Distinct	6
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Paseo	202
VTT	109
Velo	109
Amarilla	94
Carretera	93

Length

Max length	9
Median length	5
Mean length	5.732857143
Min length	3

Characters and Unicode

Total characters	4013
Distinct characters	16
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Carretera
2nd row	Carretera
3rd row	Carretera
4th row	Carretera
5th row	Carretera

Value	Count	Frequency (%)
Paseo	202	28.9%
VTT	109	15.6%
Velo	109	15.6%
Amarilla	94	13.4%
Carretera	93	13.3%
Montana	93	13.3%

Histogram of lengths of the category

Value	Count	Frequency (%)
paseo	202	28.9%
vtt	109	15.6%
velo	109	15.6%
amarilla	94	13.4%
carretera	93	13.3%
montana	93	13.3%

Most occurring characters

Value	Count	Frequency (%)
a	762	19.0%
e	497	12.4%
o	404	10.1%
r	373	9.3%
l	297	7.4%
V	218	5.4%
T	218	5.4%
P	202	5.0%
s	202	5.0%
t	186	4.6%
Other values (6)	654	16.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3095	77.1%
Uppercase Letter	918	22.9%

Most frequent character per category

Value	Count	Frequency (%)
a	762	24.6%
e	497	16.1%
o	404	13.1%
r	373	12.1%
l	297	9.6%
s	202	6.5%
t	186	6.0%
n	186	6.0%
m	94	3.0%
i	94	3.0%

Value	Count	Frequency (%)
V	218	23.7%
T	218	23.7%
P	202	22.0%
A	94	10.2%
C	93	10.1%
M	93	10.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4013	100.0%

Most frequent character per script

Value	Count	Frequency (%)
a	762	19.0%
e	497	12.4%
o	404	10.1%
r	373	9.3%
l	297	7.4%
V	218	5.4%
T	218	5.4%
P	202	5.0%
s	202	5.0%
t	186	4.6%
Other values (6)	654	16.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4013	100.0%

Most frequent character per block

Value	Count	Frequency (%)
a	762	19.0%
e	497	12.4%
o	404	10.1%
r	373	9.3%
l	297	7.4%
V	218	5.4%
T	218	5.4%
P	202	5.0%
s	202	5.0%
t	186	4.6%
Other values (6)	654	16.3%

Discount Band
Categorical

Distinct	4
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

High	245
Medium	242
Low	160
None	53

Length

Max length	6
Median length	4
Mean length	4.462857143
Min length	3

Characters and Unicode

Total characters	3124
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	None
2nd row	None
3rd row	None
4th row	None
5th row	None

Value	Count	Frequency (%)
High	245	35.0%
Medium	242	34.6%
Low	160	22.9%
None	53	7.6%

Histogram of lengths of the category

Value	Count	Frequency (%)
high	245	35.0%
medium	242	34.6%
low	160	22.9%
none	53	7.6%

Most occurring characters

Value	Count	Frequency (%)
i	487	15.6%
e	295	9.4%
H	245	7.8%
g	245	7.8%
h	245	7.8%
M	242	7.7%
d	242	7.7%
u	242	7.7%
m	242	7.7%
o	213	6.8%
Other values (4)	426	13.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	2424	77.6%
Uppercase Letter	700	22.4%

Most frequent character per category

Value	Count	Frequency (%)
i	487	20.1%
e	295	12.2%
g	245	10.1%
h	245	10.1%
d	242	10.0%
u	242	10.0%
m	242	10.0%
o	213	8.8%
w	160	6.6%
n	53	2.2%

Value	Count	Frequency (%)
H	245	35.0%
M	242	34.6%
L	160	22.9%
N	53	7.6%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3124	100.0%

Most frequent character per script

Value	Count	Frequency (%)
i	487	15.6%
e	295	9.4%
H	245	7.8%
g	245	7.8%
h	245	7.8%
M	242	7.7%
d	242	7.7%
u	242	7.7%
m	242	7.7%
o	213	6.8%
Other values (4)	426	13.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3124	100.0%

Most frequent character per block

Value	Count	Frequency (%)
i	487	15.6%
e	295	9.4%
H	245	7.8%
g	245	7.8%
h	245	7.8%
M	242	7.7%
d	242	7.7%
u	242	7.7%
m	242	7.7%
o	213	6.8%
Other values (4)	426	13.6%

Units Sold
Real number (ℝ_≥0)

Distinct	510
Distinct (%)	72.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	1608.294286
Minimum	200
Maximum	4492.5
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	200
5-th percentile	344.95
Q1	905
median	1542.5
Q3	2229.125
95-th percentile	2935.95
Maximum	4492.5
Range	4292.5
Interquartile range (IQR)	1324.125

Descriptive statistics

Standard deviation	867.4278591
Coefficient of variation (CV)	0.5393464783
Kurtosis	-0.3153179967
Mean	1608.294286
Median Absolute Deviation (MAD)	655.5
Skewness	0.4361535619
Sum	1125806
Variance	752431.0907
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
727	5	0.7%
1916	4	0.6%
1496	4	0.6%
663	4	0.6%
2844	4	0.6%
1743	4	0.6%
386	3	0.4%
1366	3	0.4%
2145	3	0.4%
1123	3	0.4%
Other values (500)	663	94.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
200	1	0.1%
214	2	0.3%
218	1	0.1%
241	2	0.3%
245	1	0.1%

Value	Count	Frequency (%)
4492.5	1	0.1%
4251	1	0.1%
4243.5	1	0.1%
4219.5	1	0.1%
4026	1	0.1%

Manufacturing Price
Real number (ℝ_≥0)

Distinct	6
Distinct (%)	0.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	96.47714286
Minimum	3
Maximum	260
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	3
5-th percentile	3
Q1	5
median	10
Q3	250
95-th percentile	260
Maximum	260
Range	257
Interquartile range (IQR)	245

Descriptive statistics

Standard deviation	108.6026122
Coefficient of variation (CV)	1.125682301
Kurtosis	-1.42896268
Mean	96.47714286
Median Absolute Deviation (MAD)	7
Skewness	0.5925839516
Sum	67534
Variance	11794.52737
Monotocity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
10	202	28.9%
120	109	15.6%
250	109	15.6%
260	94	13.4%
3	93	13.3%
5	93	13.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
3	93	13.3%
5	93	13.3%
10	202	28.9%
120	109	15.6%
250	109	15.6%

Value	Count	Frequency (%)
260	94	13.4%
250	109	15.6%
120	109	15.6%
10	202	28.9%
5	93	13.3%

Sale Price
Real number (ℝ_≥0)

Distinct	7
Distinct (%)	1.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	118.4285714
Minimum	7
Maximum	350
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	7
5-th percentile	7
Q1	12
median	20
Q3	300
95-th percentile	350
Maximum	350
Range	343
Interquartile range (IQR)	288

Descriptive statistics

Standard deviation	136.7755146
Coefficient of variation (CV)	1.154919906
Kurtosis	-1.176789008
Mean	118.4285714
Median Absolute Deviation (MAD)	13
Skewness	0.7712818708
Sum	82900
Variance	18707.54139
Monotocity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
7	100	14.3%
12	100	14.3%
15	100	14.3%
20	100	14.3%
125	100	14.3%
300	100	14.3%
350	100	14.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
7	100	14.3%
12	100	14.3%
15	100	14.3%
20	100	14.3%
125	100	14.3%

Value	Count	Frequency (%)
350	100	14.3%
300	100	14.3%
125	100	14.3%
20	100	14.3%
15	100	14.3%

Gross Sales
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	550
Distinct (%)	78.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	182759.4264
Minimum	1799
Maximum	1207500
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	1799
5-th percentile	5193.05
Q1	17391.75
median	37980
Q3	279025
95-th percentile	754250
Maximum	1207500
Range	1205701
Interquartile range (IQR)	261633.25

Descriptive statistics

Standard deviation	254262.2844
Coefficient of variation (CV)	1.391240328
Kurtosis	2.054300583
Mean	182759.4264
Median Absolute Deviation (MAD)	30747.5
Skewness	1.673921656
Sum	127931598.5
Variance	6.464930926 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
82875	3	0.4%
26145	3	0.4%
22710	3	0.4%
37050	3	0.4%
738000	3	0.4%
4404	3	0.4%
18540	2	0.3%
42660	2	0.3%
411600	2	0.3%
7248	2	0.3%
Other values (540)	674	96.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1799	1	0.1%
1841	2	0.3%
1960	2	0.3%
2051	1	0.1%
2520	2	0.3%

Value	Count	Frequency (%)
1207500	1	0.1%
1140750	1	0.1%
1138050	1	0.1%
1048500	1	0.1%
1038100	2	0.3%

Discounts
Real number (ℝ_≥0)

ZEROS

Distinct	515
Distinct (%)	73.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	13150.35463
Minimum	0
Maximum	149677.5
Zeros	53
Zeros (%)	7.6%
Memory size	5.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	800.32
median	2585.25
Q3	15956.34375
95-th percentile	62832
Maximum	149677.5
Range	149677.5
Interquartile range (IQR)	15156.02375

Descriptive statistics

Standard deviation	22962.92877
Coefficient of variation (CV)	1.746183234
Kurtosis	7.905712444
Mean	13150.35463
Median Absolute Deviation (MAD)	2328.57
Skewness	2.685038938
Sum	9205248.24
Variance	527296097.9
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	53	7.6%
5690	3	0.4%
1218.6	3	0.4%
20139	3	0.4%
6822.5	2	0.3%
29538	2	0.3%
2663	2	0.3%
13244	2	0.3%
1037.7	2	0.3%
4826.25	2	0.3%
Other values (505)	626	89.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	53	7.6%
18.41	1	0.1%
25.34	1	0.1%
44.73	1	0.1%
48.15	1	0.1%

Value	Count	Frequency (%)
149677.5	1	0.1%
125820	1	0.1%
119756	2	0.3%
115830	1	0.1%
112927.5	1	0.1%

Sales
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	559
Distinct (%)	79.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	169609.0718
Minimum	1655.08
Maximum	1159200
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	1655.08
5-th percentile	4535.65
Q1	15928
median	35540.2
Q3	261077.5
95-th percentile	683574.75
Maximum	1159200
Range	1157544.92
Interquartile range (IQR)	245149.5

Descriptive statistics

Standard deviation	236726.3469
Coefficient of variation (CV)	1.395717484
Kurtosis	2.188633088
Mean	169609.0718
Median Absolute Deviation (MAD)	28716.7
Skewness	1.696295217
Sum	118726350.3
Variance	5.603936332 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
83600	2	0.3%
16748.55	2	0.3%
260580	2	0.3%
206852.5	2	0.3%
15056.72	2	0.3%
30072.48	2	0.3%
4280.4	2	0.3%
986811	2	0.3%
10575.72	2	0.3%
1685.6	2	0.3%
Other values (549)	680	97.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1655.08	1	0.1%
1685.6	2	0.3%
1730.54	1	0.1%
1763.86	1	0.1%
1822.59	1	0.1%

Value	Count	Frequency (%)
1159200	1	0.1%
1038082.5	1	0.1%
1035625.5	1	0.1%
1017338	2	0.3%
986811	2	0.3%

COGS
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	545
Distinct (%)	77.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	145475.2114
Minimum	918
Maximum	950625
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	918
5-th percentile	2449.5
Q1	7490
median	22506.25
Q3	245607.5
95-th percentile	608643.75
Maximum	950625
Range	949707
Interquartile range (IQR)	238117.5

Descriptive statistics

Standard deviation	203865.5061
Coefficient of variation (CV)	1.401376249
Kurtosis	1.608462973
Mean	145475.2114
Median Absolute Deviation (MAD)	19576.25
Skewness	1.549047562
Sum	101832648
Variance	4.156114458 × 10¹⁰
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
17430	4	0.6%
15140	3	0.4%
79560	3	0.4%
615000	3	0.4%
8655	3	0.4%
24700	3	0.4%
1101	3	0.4%
545250	2	0.3%
158750	2	0.3%
6630	2	0.3%
Other values (535)	672	96.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
918	1	0.1%
1101	3	0.4%
1158	2	0.3%
1230	2	0.3%
1285	1	0.1%

Value	Count	Frequency (%)
950625	1	0.1%
948375	1	0.1%
897000	1	0.1%
873750	1	0.1%
771160	2	0.3%

Profit
Real number (ℝ)

Distinct	557
Distinct (%)	79.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	24133.86037
Minimum	-40617.5
Maximum	262200
Zeros	5
Zeros (%)	0.7%
Memory size	5.6 KiB

Quantile statistics

Minimum	-40617.5
5-th percentile	-7849.25
Q1	2805.96
median	9242.2
Q3	22662
95-th percentile	117138.1
Maximum	262200
Range	302817.5
Interquartile range (IQR)	19856.04

Descriptive statistics

Standard deviation	42760.62656
Coefficient of variation (CV)	1.771810473
Kurtosis	8.678616216
Mean	24133.86037
Median Absolute Deviation (MAD)	7383.075
Skewness	2.712151264
Sum	16893702.26
Variance	1828471184
Monotocity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5	0.7%
39072	2	0.3%
2216.74	2	0.3%
7584.5	2	0.3%
6878	2	0.3%
20420.4	2	0.3%
4773.25	2	0.3%
3010.8	2	0.3%
6802.08	2	0.3%
11474.4	2	0.3%
Other values (547)	677	96.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-40617.5	1	0.1%
-38046.25	1	0.1%
-35550	1	0.1%
-35262.5	1	0.1%
-33522.5	1	0.1%

Value	Count	Frequency (%)
262200	1	0.1%
247500	1	0.1%
246178	2	0.3%
238791	2	0.3%
236716	2	0.3%

Date
Date

Distinct	16
Distinct (%)	2.3%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

Minimum	2013-09-01 00:00:00
Maximum	2014-12-01 00:00:00

Histogram

Histogram with fixed size bins (bins=16)

Month Number
Real number (ℝ_≥0)

Distinct	12
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%

Mean	7.9
Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Memory size	5.6 KiB

Quantile statistics

Minimum	1
5-th percentile	1.95
Q1	5.75
median	9
Q3	10.25
95-th percentile	12
Maximum	12
Range	11
Interquartile range (IQR)	4.5

Descriptive statistics

Standard deviation	3.37732064
Coefficient of variation (CV)	0.4275089418
Kurtosis	-0.8791598187
Mean	7.9
Median Absolute Deviation (MAD)	2.5
Skewness	-0.5782921541
Sum	5530
Variance	11.40629471
Monotocity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
10	140	20.0%
12	105	15.0%
6	70	10.0%
9	70	10.0%
11	70	10.0%
1	35	5.0%
2	35	5.0%
3	35	5.0%
4	35	5.0%
5	35	5.0%
Other values (2)	70	10.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	35	5.0%
2	35	5.0%
3	35	5.0%
4	35	5.0%
5	35	5.0%

Value	Count	Frequency (%)
12	105	15.0%
11	70	10.0%
10	140	20.0%
9	70	10.0%
8	35	5.0%

Month Name
Categorical

Distinct	12
Distinct (%)	1.7%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

October	140
December	105
November	70
September	70
June	70
Other values (7)	245

Length

Max length	9
Median length	7
Mean length	6.6
Min length	3

Characters and Unicode

Total characters	4620
Distinct characters	26
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	January
2nd row	January
3rd row	June
4th row	June
5th row	June

Value	Count	Frequency (%)
October	140	20.0%
December	105	15.0%
November	70	10.0%
September	70	10.0%
June	70	10.0%
February	35	5.0%
July	35	5.0%
May	35	5.0%
April	35	5.0%
March	35	5.0%
Other values (2)	70	10.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
october	140	20.0%
december	105	15.0%
november	70	10.0%
june	70	10.0%
september	70	10.0%
january	35	5.0%
july	35	5.0%
august	35	5.0%
february	35	5.0%
april	35	5.0%
Other values (2)	70	10.0%

Most occurring characters

Value	Count	Frequency (%)
e	910	19.7%
r	560	12.1%
b	420	9.1%
c	280	6.1%
u	245	5.3%
m	245	5.3%
t	245	5.3%
o	210	4.5%
a	175	3.8%
J	140	3.0%
Other values (16)	1190	25.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3920	84.8%
Uppercase Letter	700	15.2%

Most frequent character per category

Value	Count	Frequency (%)
e	910	23.2%
r	560	14.3%
b	420	10.7%
c	280	7.1%
u	245	6.2%
m	245	6.2%
t	245	6.2%
o	210	5.4%
a	175	4.5%
y	140	3.6%
Other values (8)	490	12.5%

Value	Count	Frequency (%)
J	140	20.0%
O	140	20.0%
D	105	15.0%
M	70	10.0%
A	70	10.0%
S	70	10.0%
N	70	10.0%
F	35	5.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4620	100.0%

Most frequent character per script

Value	Count	Frequency (%)
e	910	19.7%
r	560	12.1%
b	420	9.1%
c	280	6.1%
u	245	5.3%
m	245	5.3%
t	245	5.3%
o	210	4.5%
a	175	3.8%
J	140	3.0%
Other values (16)	1190	25.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4620	100.0%

Most frequent character per block

Value	Count	Frequency (%)
e	910	19.7%
r	560	12.1%
b	420	9.1%
c	280	6.1%
u	245	5.3%
m	245	5.3%
t	245	5.3%
o	210	4.5%
a	175	3.8%
J	140	3.0%
Other values (16)	1190	25.8%

Year
Categorical

Distinct	2
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	5.6 KiB

2014	525
2013	175

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	2800
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2014
2nd row	2014
3rd row	2014
4th row	2014
5th row	2014

Value	Count	Frequency (%)
2014	525	75.0%
2013	175	25.0%

Histogram of lengths of the category

Value	Count	Frequency (%)
2014	525	75.0%
2013	175	25.0%

Most occurring characters

Value	Count	Frequency (%)
2	700	25.0%
0	700	25.0%
1	700	25.0%
4	525	18.8%
3	175	6.2%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2800	100.0%

Most frequent character per category

Value	Count	Frequency (%)
2	700	25.0%
0	700	25.0%
1	700	25.0%
4	525	18.8%
3	175	6.2%

Most occurring scripts

Value	Count	Frequency (%)
Common	2800	100.0%

Most frequent character per script

Value	Count	Frequency (%)
2	700	25.0%
0	700	25.0%
1	700	25.0%
4	525	18.8%
3	175	6.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2800	100.0%

Most frequent character per block

Value	Count	Frequency (%)
2	700	25.0%
0	700	25.0%
1	700	25.0%
4	525	18.8%
3	175	6.2%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	Segment	Country	Product	Discount Band	Units Sold	Manufacturing Price	Sale Price	Gross Sales	Sales	COGS	Profit	Date	Month Number	Month Name	Year
0	Government	Canada	Carretera	None	1618.5	3	20	32370.0	32370.0	16185.0	16185.0	2014-01-01	1	January	2014
1	Government	Germany	Carretera	None	1321.0	3	20	26420.0	26420.0	13210.0	13210.0	2014-01-01	1	January	2014
2	Midmarket	France	Carretera	None	2178.0	3	15	32670.0	32670.0	21780.0	10890.0	2014-06-01	6	June	2014
3	Midmarket	Germany	Carretera	None	888.0	3	15	13320.0	13320.0	8880.0	4440.0	2014-06-01	6	June	2014
4	Midmarket	Mexico	Carretera	None	2470.0	3	15	37050.0	37050.0	24700.0	12350.0	2014-06-01	6	June	2014
5	Government	Germany	Carretera	None	1513.0	3	350	529550.0	529550.0	393380.0	136170.0	2014-12-01	12	December	2014
6	Midmarket	Germany	Montana	None	921.0	5	15	13815.0	13815.0	9210.0	4605.0	2014-03-01	3	March	2014
7	Channel Partners	Canada	Montana	None	2518.0	5	12	30216.0	30216.0	7554.0	22662.0	2014-06-01	6	June	2014
8	Government	France	Montana	None	1899.0	5	20	37980.0	37980.0	18990.0	18990.0	2014-06-01	6	June	2014
9	Channel Partners	Germany	Montana	None	1545.0	5	12	18540.0	18540.0	4635.0	13905.0	2014-06-01	6	June	2014

Last rows

	Segment	Country	Product	Discount Band	Units Sold	Manufacturing Price	Sale Price	Gross Sales	Discounts	Sales	COGS	Profit	Date	Month Number	Month Name	Year
690	Government	United States of America	VTT	High	267.0	250	20	5340.0	801.00	4539.00	2670.0	1869.00	2013-10-01	10	October	2013
691	Midmarket	Germany	VTT	High	1175.0	250	15	17625.0	2643.75	14981.25	11750.0	3231.25	2014-10-01	10	October	2014
692	Enterprise	Canada	VTT	High	2954.0	250	125	369250.0	55387.50	313862.50	354480.0	-40617.50	2013-11-01	11	November	2013
693	Enterprise	Germany	VTT	High	552.0	250	125	69000.0	10350.00	58650.00	66240.0	-7590.00	2014-11-01	11	November	2014
694	Government	France	VTT	High	293.0	250	20	5860.0	879.00	4981.00	2930.0	2051.00	2014-12-01	12	December	2014
695	Small Business	France	Amarilla	High	2475.0	260	300	742500.0	111375.00	631125.00	618750.0	12375.00	2014-03-01	3	March	2014
696	Small Business	Mexico	Amarilla	High	546.0	260	300	163800.0	24570.00	139230.00	136500.0	2730.00	2014-10-01	10	October	2014
697	Government	Mexico	Montana	High	1368.0	5	7	9576.0	1436.40	8139.60	6840.0	1299.60	2014-02-01	2	February	2014
698	Government	Canada	Paseo	High	723.0	10	7	5061.0	759.15	4301.85	3615.0	686.85	2014-04-01	4	April	2014
699	Channel Partners	United States of America	VTT	High	1806.0	250	12	21672.0	3250.80	18421.20	5418.0	13003.20	2014-05-01	5	May	2014

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows